Abstract

Background

Navigating the intricacies of discovering unique and functional antibody binders for in vitro diagnostic development comes with several technological challenges, such as limited diversity of antibody repertoires, functional screening challenges, and the absence of suitable in vitro models. A proteomics-driven strategy to antibody discovery is a promising solution to overcome these obstacles by facilitating polyclonal to monoclonal antibody conversion.

De novo polyclonal antibody sequencing utilizes mass spectrometry and machine-learning driven bioinformatics to obtain complete antibody sequences from immunoserum or purified protein samples. This approach investigates the entire circulating antibody repertoire at the protein level, thereby broadening the spectrum of potential candidates. It further facilitates functional selection by enabling antibody purification and enrichment techniques. This capability facilitates the identification of antibodies possessing unique functions, crucial for subsequent downstream development.

We demonstrate the application and de novo polyclonal antibody sequencing using mass spectrometry and machine learning bioinformatics to enable the next generation of antibody discovery.

Methods

In this study, we employed a novel mass spectrometry-based approach, REpAb, to de novo sequence polyclonal antibodies directly from the immunized serum of animals or human patients. REpAb integrates mass spectrometry with machine learning-based bioinformatics to de novo sequence and assemble monoclonal antibodies from a polyclonal mixture. Protein lysates underwent analysis using an Orbitrap EclipseTM Series instrument (ThermoFisher Scientific, CA, US) coupled with the LC Evosep One (Evosep, Denmark).

Results

De novo polyclonal sequencing with REpAb yielded unique antibody binders not found in splenocytes or peripheral blood mononuclear cells (PBMCs). De novo antibody sequencing-discovered antibody sequences from naturally exposed humans showed unrestricted germline usage, compared to restricted germline used in antigen-immunized animals. Additionally, a proteomics-based approach for antibody discovery enables functional antibody selection through standard protein A/G purification, followed by negative and positive selection enrichment strategies to isolate antibody clones specific to the region of interest on the antigen.

Conclusions

Sequencing antibodies at the protein level directly reflects the circulating antibody repertoires, which expands the antibody diversity from the BCR repertoire. Proteomic-based antibody discovery empowers the functional selection of antibodies via meticulously designed enrichment strategies. This approach allows for the identification of a diverse pool of candidates possessing specific functions, such as anti-idiotypic features.

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